statistics-0.14.0.2: A library of statistical types, data, and functions

Statistics.Distribution.Normal

Contents

Description

The normal distribution. This is a continuous probability distribution that describes data that cluster around a mean.

Synopsis

# Documentation

The normal distribution.

Instances

 Source # Methods Source # Methodsgfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> NormalDistribution -> c NormalDistribution #gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c NormalDistribution #dataCast1 :: Typeable (* -> *) t => (forall d. Data d => c (t d)) -> Maybe (c NormalDistribution) #dataCast2 :: Typeable (* -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c NormalDistribution) #gmapT :: (forall b. Data b => b -> b) -> NormalDistribution -> NormalDistribution #gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> NormalDistribution -> r #gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> NormalDistribution -> r #gmapQ :: (forall d. Data d => d -> u) -> NormalDistribution -> [u] #gmapQi :: Int -> (forall d. Data d => d -> u) -> NormalDistribution -> u #gmapM :: Monad m => (forall d. Data d => d -> m d) -> NormalDistribution -> m NormalDistribution #gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> NormalDistribution -> m NormalDistribution #gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> NormalDistribution -> m NormalDistribution # Source # Methods Source # MethodsshowList :: [NormalDistribution] -> ShowS # Source # Associated Typestype Rep NormalDistribution :: * -> * # Methods Source # Methods Source # Methods Source # MethodsputList :: [NormalDistribution] -> Put # Source # MethodsgenContVar :: PrimMonad m => NormalDistribution -> Gen (PrimState m) -> m Double Source # Source # Methods Source # Methods Source # Methods Source # Methods Source # Methods Source # Methods Source # Methods Source # Methods Source # Variance is estimated using maximum likelihood method (biased estimation).Returns Nothing if sample contains less than one element or variance is zero (all elements are equal) Methods Source # type Rep NormalDistribution = D1 (MetaData "NormalDistribution" "Statistics.Distribution.Normal" "statistics-0.14.0.2-9wDz1lVU92ZDJSrAe5uHzb" False) (C1 (MetaCons "ND" PrefixI True) ((:*:) ((:*:) (S1 (MetaSel (Just Symbol "mean") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)) (S1 (MetaSel (Just Symbol "stdDev") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double))) ((:*:) (S1 (MetaSel (Just Symbol "ndPdfDenom") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)) (S1 (MetaSel (Just Symbol "ndCdfDenom") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)))))

# Constructors

Arguments

 :: Double Mean of distribution -> Double Standard deviation of distribution -> NormalDistribution

Create normal distribution from parameters.

IMPORTANT: prior to 0.10 release second parameter was variance not standard deviation.

Arguments

 :: Double Mean of distribution -> Double Standard deviation of distribution -> Maybe NormalDistribution

Create normal distribution from parameters.

IMPORTANT: prior to 0.10 release second parameter was variance not standard deviation.

Standard normal distribution with mean equal to 0 and variance equal to 1